Image Analysis Based Grading of Bladder Carcinoma. Comparison of Object, Texture and Graph Based Methods and Their Reproducibility

The possibility that computerized image analysis could increase the reproducibility of grading of bladder carcinoma as compared to conventional subjective grading made by pathologists was investigated. Object, texture and graph based analysis were carried out from Feulgen stained histological tissue...

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Main Authors: Heung‐Kook Choi, Torsten Jarkrans, Ewert Bengtsson, Janos Vasko, Kenneth Wester, Per-Uno Malmström, Christer Busch
Format: Article
Language:English
Published: Wiley 1997-01-01
Series:Analytical Cellular Pathology
Online Access:http://dx.doi.org/10.1155/1997/147187
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author Heung‐Kook Choi
Torsten Jarkrans
Ewert Bengtsson
Janos Vasko
Kenneth Wester
Per-Uno Malmström
Christer Busch
author_facet Heung‐Kook Choi
Torsten Jarkrans
Ewert Bengtsson
Janos Vasko
Kenneth Wester
Per-Uno Malmström
Christer Busch
author_sort Heung‐Kook Choi
collection DOAJ
description The possibility that computerized image analysis could increase the reproducibility of grading of bladder carcinoma as compared to conventional subjective grading made by pathologists was investigated. Object, texture and graph based analysis were carried out from Feulgen stained histological tissue sections. The object based features were extracted from gray scale images, binary images obtained by thresholding the nuclei and several other images derived through image processing operations. The textural features were based on the spatial gray‐tone co‐occurrence probability matrices and the graph based features were extracted from the minimum spanning trees connecting all nuclei. The large numbers of extracted features were evaluated in relation to subjective grading and to factors related to prognosis using multivariate statistical methods and multilayer backpropagation neural networks. All the methods were originally developed and tested on material from one patient and then tested for reproducibility on entirely different patient material. The results indicate reasonably good reproducibility for the best sets of features. In addition, image analysis based grading showed almost identical correlation to mitotic density and expression of p53 protein as subjective grading. It should thus be possible to use this kind of image analysis as a prognostic tool for bladder carcinoma.
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institution Kabale University
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publishDate 1997-01-01
publisher Wiley
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series Analytical Cellular Pathology
spelling doaj-art-65f5e5e9f5794c92b27d6b3619ac920d2025-02-03T06:08:30ZengWileyAnalytical Cellular Pathology0921-89121878-36511997-01-0115111810.1155/1997/147187Image Analysis Based Grading of Bladder Carcinoma. Comparison of Object, Texture and Graph Based Methods and Their ReproducibilityHeung‐Kook Choi0Torsten Jarkrans1Ewert Bengtsson2Janos Vasko3Kenneth Wester4Per-Uno Malmström5Christer Busch6Centre for Image Analysis, Uppsala University, Uppsala, SwedenCentre for Image Analysis, Uppsala University, Uppsala, SwedenCentre for Image Analysis, Uppsala University, Uppsala, SwedenDepartment of Pathology, Umeå University, Umeå, SwedenDepartment of Pathology, University Hospital, Uppsala, SwedenDepartment of Urology, University Hospital, Uppsala, SwedenDepartment of Pathology, University Hospital, Uppsala, SwedenThe possibility that computerized image analysis could increase the reproducibility of grading of bladder carcinoma as compared to conventional subjective grading made by pathologists was investigated. Object, texture and graph based analysis were carried out from Feulgen stained histological tissue sections. The object based features were extracted from gray scale images, binary images obtained by thresholding the nuclei and several other images derived through image processing operations. The textural features were based on the spatial gray‐tone co‐occurrence probability matrices and the graph based features were extracted from the minimum spanning trees connecting all nuclei. The large numbers of extracted features were evaluated in relation to subjective grading and to factors related to prognosis using multivariate statistical methods and multilayer backpropagation neural networks. All the methods were originally developed and tested on material from one patient and then tested for reproducibility on entirely different patient material. The results indicate reasonably good reproducibility for the best sets of features. In addition, image analysis based grading showed almost identical correlation to mitotic density and expression of p53 protein as subjective grading. It should thus be possible to use this kind of image analysis as a prognostic tool for bladder carcinoma.http://dx.doi.org/10.1155/1997/147187
spellingShingle Heung‐Kook Choi
Torsten Jarkrans
Ewert Bengtsson
Janos Vasko
Kenneth Wester
Per-Uno Malmström
Christer Busch
Image Analysis Based Grading of Bladder Carcinoma. Comparison of Object, Texture and Graph Based Methods and Their Reproducibility
Analytical Cellular Pathology
title Image Analysis Based Grading of Bladder Carcinoma. Comparison of Object, Texture and Graph Based Methods and Their Reproducibility
title_full Image Analysis Based Grading of Bladder Carcinoma. Comparison of Object, Texture and Graph Based Methods and Their Reproducibility
title_fullStr Image Analysis Based Grading of Bladder Carcinoma. Comparison of Object, Texture and Graph Based Methods and Their Reproducibility
title_full_unstemmed Image Analysis Based Grading of Bladder Carcinoma. Comparison of Object, Texture and Graph Based Methods and Their Reproducibility
title_short Image Analysis Based Grading of Bladder Carcinoma. Comparison of Object, Texture and Graph Based Methods and Their Reproducibility
title_sort image analysis based grading of bladder carcinoma comparison of object texture and graph based methods and their reproducibility
url http://dx.doi.org/10.1155/1997/147187
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AT ewertbengtsson imageanalysisbasedgradingofbladdercarcinomacomparisonofobjecttextureandgraphbasedmethodsandtheirreproducibility
AT janosvasko imageanalysisbasedgradingofbladdercarcinomacomparisonofobjecttextureandgraphbasedmethodsandtheirreproducibility
AT kennethwester imageanalysisbasedgradingofbladdercarcinomacomparisonofobjecttextureandgraphbasedmethodsandtheirreproducibility
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